课程概况
Visual representations generated by statistical models help us to make sense of large, complex datasets through interactive exploration, thereby enabling big data to realize its potential for informing decisions. This specialization covers techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science to enhance the understanding of complex data.
课程大纲
第 1 门课程
Introduction to Data Exploration and Visualization
课程概述
This course answers the questions, What is data visualization and What is the power of visualization? It also introduces core concepts such as dataset elements, data warehouses and exploratory querying, and combinations of visual variables for graphic usefulness, as well as the types of statistical graphs, tools that are essential to exploratory data analysis.
第 2 门课程
Multivariate and Geographical Data Analysis
课程概述
Covering the tools and techniques of both multivariate and geographical analysis, this course provides hands-on experience visualizing data that represents multiple variables. This course will use statistical techniques and software to develop and analyze geographical knowledge.
第 3 门课程
Temporal and Hierarchical Data Analysis
课程概述
Data repositories in which cases are related to subcases are identified as hierarchical. This course covers the representation schemes of hierarchies and algorithms that enable analysis of hierarchical data, as well as provides opportunities to apply several methods of analysis.
第 4 门课程
Additional Tools Used for Data Visualization
课程概述
This course will expose learners to additional tools that can be used to perform Data Visualization. In particular, the courses focuses on Tableau, a state-of-the-art visualization package. In this course, the visualization concepts from previous courses are reinforced and the Tableau software is introduced through replication of the visualizations built in previous courses.
课程项目
Designed to help you practice and apply the skills you learn.
Project 1: Analyzing Theme Park Patronage
Project 2: Analyzing Wait Times and Dynamics of Theme Park Patronage
Project 3: Exploring and Clustering Trajectories in a Theme Park
Project 4: Finding Commonalities Between Theme Park Patrons
常见问题
退款政策是如何规定的？
您可以在付款后的 14 天内或在课程或专项课程开课后的 14 天内（以较晚者为准）申请退款。获得课程证书后，您便无法再退款；即使您在 14 天内完成了课程，也是如此。
请阅读完整的退款政策。
我可以只注册一门课程吗？我对整个专项课程不感兴趣。
要注册单门课程，请在目录中搜索相应的课程标题。
当当您订阅属于专项课程的课程时，您将自动订阅整个专项课程。如果您仅对单门课程感兴趣，您将需要在完成本课程后取消您的订阅，以停止定期缴纳每月费用。
可以申请助学金吗？
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
How long does it take to complete the Specialization?
Time to completion can vary based on your schedule and experience level, most individual courses, in which this Specialization has 4, will take about a month to complete if you devote 2-5 hours per week.
What background knowledge is necessary?
Basic statistics and computer science knowledge including computer organization and architecture, discrete mathematics, data structures, and algorithms
Knowledge of high-level programming languages (e.g., C++, Java) and scripting language (e.g., Python), Jupyter Notebooks
Do I need to take the courses in a specific order?
No, courses may be taken in any order.
Will I earn university credit for completing the Specialization?
All courses in this Specialization form the lecture and skill practice component of a corresponding course in ASU’s online Master of Computer Science Degree. You can apply to the degree program either before or after you begin the Specialization.
What will I be able to do upon completing the Specialization?
Learners completing this specialization will be able to:
Develop exploratory data analysis and visualization tools using Python and Jupyter notebooks
Apply design principles for a variety of statistical graphics and visualizations including scatterplots, line charts, histograms, and choropleth maps
Combine exploratory queries, graphics, and interaction to develop functional tools for exploratory data analysis and visualization
